You can monitor how data that is subject to data quality SLA rules comply with these rules. In addition, you can see the status of remediation tasks for resolving data quality issues that are reported by violated data quality SLA rules.
To focus quality improvement efforts on the data that is most important for your organization, you can create data quality SLA rules and assess data quality SLA rule compliance as part of metadata enrichment.
Each assessment of an SLA rule generates an entry in the SLA compliance report of a monitored asset independent of whether the rule conditions were violated. SLA compliance reports are part of a data asset's quality information that is available from the enrichment results or on the asset's Data quality page in a project.
Depending on the configuration of a data quality SLA rule, a data quality remediation workflow might be initiated if the data asset violates this rule. The number and status of remediation tasks is also part of the data asset's quality information.
Monitor data quality checks and SLA rule violations by using IBM Databand
Data quality checks and data quality SLA rules help ensure that trustworthy and validated data is shared in a data marketplace.
To get notifications for any issue in the data quality process, you can use the monitoring and alerting features that IBM Databand provides. Set up a monitored data quality pipeline in IBM Databand that can trigger custom alerts for data quality degradation in any step of the pipeline.
You can download the sample code and detailed instructions for setting up this integration from this GitHub repository:
IBM Knowledge Catalog data quality and IBM Databand integration demo
Learn more
- Data quality SLA rules
- Data quality analysis results
- IBM Knowledge Catalog data quality and IBM Databand integration demo
Parent topic: Managing data quality